Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...
Analytics Insight

Top PyTorch Courses for Learning in 2026

Overview PyTorch courses focus strongly on real-world Deep Learning projects and production skills.Transformer models and NLP training are now core parts of mos ...

Guide Labs debuts a new kind of interpretable LLM

The company open-sourced an 8 billion parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...
Frontiers

Hybrid Mechanistic–AI Modeling with Physics-Trained Neural Networks for Patient Digital Twins

Patient digital twins aim to create computational replicas of an individual’s physiology that can predict disease trajectories and treatment response.
American Institute of Physics

Using deep learning to better forecast tropical cyclone tracks and intensities

Integrating deep learning with traditional forecasting techniques can improve early warning systems by capitalizing on each ...
ascopubs.org

Deep-Learning Model for Real-Time Prediction of Recurrence in Early-Stage Non–Small Cell Lung Cancer: A Multimodal Approach (RADAR CARE Study)

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
EurekAlert!

Interpretability in deep learning for finance: A case study for the Heston model

CNN architecture summary: The first dimension in all the layers “?” refers to the batch size. It is left as an unknown or unspecified variable within the network architecture so that it can be chosen ...